In the reproduction of copies of an original from video image data created, for example, by electronic raster input scanning from an original document, one is faced with the limited resolution capabilities of the reproducing system and the fact that output devices are mostly binary. This is particularly evident when attempting to reproduce half-tones, lines and continuous tone images. Of course, an image data processing system may be tailored so as to offset the limited resolution capabilities of the reproducing apparatus used, but this is difficult due to the divergent processing needs required by the different types of image which may be encountered. In this respect, it should be understood that the image content of the original document may consist entirely of high frequency half-tones, low frequency half-tones, continuous tones, or line copy, or a combination, in some unknown degree, of some or all of the above. In the face of these possibilities, optimizing the image processing system for one image type in an effort to offset the limitations in the resolution capability of the reproducing apparatus used, may not be possible, requiring a compromise choice which may not produce acceptable results. Thus, for example, where one optimizes the system for low frequency half-tones, it is often at the expense of degraded reproduction of high frequency half-tones, or of line copy, and vice versa.
In U.S. Pat. No. 4,194,221 to Stoffel, this problem was addressed by applying a discrimination function instructing the image processing system as to the type of image data present and particularly, an auto correlation function to the stream of pixel data, to determine the existence of high frequency half-tone image data. Such a function is expressed as: ##EQU2## where n=the bit or pixel number;
p=the pixel voltage value; and PA1 t=the pixel position in the data stream. PA1 f(l) is the pixel intensity value; PA1 l is is a selected pixel position in the data stream.
Stoffel describes a method of processing automatically a stream of image pixels representing unknown combinations of high and low frequency half-tones, continuous tones, and/or lines to provide binary level output pixels representative of the image. The described function is applied to the stream of image pixels and, for the portions of the stream that contained high frequency half-tone image data, notes a large number of closely spaced peaks in the resultant signal. The correlator circuits described in Stoffel's referred embodiment however, are very expensive, as they must provide a digital multiplication function. Accordingly, as a practical matter, Stoffel requires as a first step, reduction of the amount of data handled, by initially thresholding image data against a single threshold value, to reduce the image to a high contrast black or white image. However, depending on the selection of the threshold as compared to the intensity of the image, significant amounts of information may be lost in the thresholding process. For example, if the threshold level is set to distinguish in the middle of the intensity range, but the image has significant variations through the darker gray levels, the thresholded result does not indicate the variations. This results in an undesirable loss of image information. While it may be possible to vary the threshold value adaptively from original to original and from image area to image area, such algorithms tend to be complicated and work well only for a restricted class of images such as line images.
GB No. 2,153,619A provides a similar determination of the type of image data. However in that case, a threshold is applied to the image data at a certain level, and subsequent to thresholding the number of transitions from light to dark within a small area is counted. The system operates on the presumption that data with a low number of transitions after thresholding is probably a high frequency half-tone or continuous tone image. The thresholding step in this method has the same undesirable effect as described for Stoffel.
Of the background interest in this area are U.S. Pat. No. 4,556,918 to Yamazaki et al. showing an arrangement assuming a periodicity of an area of half-tone dots which are thresholded against an average value derived from the area to produce a density related video signal; U.S. Pat. No. 4,251,837 to Janeway, III, which shows using a three decision mode selection for determining threshold selection based on gradient constants for each pixel; U.S. Pat. No. 4,578,714 to Sugiura et al. which shows random data added to the output signal to eliminate pseudo-outlines; U.S. Pat. No. 4,559,563 to Joiner, Jr., suggests an adaptive prediction for compressing data based on a predictor which worked best for a previous pixel block; and U.S. Pat. No. 3,294,896 to Young, Jr., teaches the usefulness of thresholding in producing an image from a binary digital transmission system.